This paper presents a comprehensive study of modelling human body blockage (the most critical challenges in fifth-generation (5G)) effects on indoor millimetre wave (mmWave) communication links at 32.5 GHz, a key frequency for 5G networks. Through controlled experiments in a laboratory environment, we analyse signal attenuation as a human subject obstructs the line-of-sight (LOS) path between transmitter and receiver, recording received power at incremental positions. To model the observed phenomena, we propose a hybrid framework integrating deterministic and statistical components: (1) a modified Double Knife-Edge Diffraction (DKED) model with Gaussian-shaped blockage attenuation (20.8 dB peak at full blockage) and reflection-induced signal enhancement (−15.0 dB peak from nearby objects), and (2) a log-normal shadowing component (σ = 11.8 dB) capturing environmental randomness. Our results reveal strong agreement between simulations and measurements, achieving a mean absolute error of 3.2 dB and a correlation coefficient R² = 0.89. The analysis demonstrates that human-induced diffraction dominates near the LOS centre, while multipath reflections significantly alter signal strength at peripheral positions. We further derive practical guidelines for 5G network design, recommending a 44.4 dB link budget safety margin to account for combined blockage and shadowing effects. This work advances indoor mmWaves channel modelling by unifying physics-based diffraction analysis with empirical reflection characterization, the framework achieves strong experimental validation and offers actionable insights for 5G network design

The advent of 5G networks has revolutionized wireless communications by unlocking unprecedented data rates through millimeter-wave (mmWave) frequencies. However, the short wavelengths of mmWave signals (e.g., 32.5 GHz) make them highly vulnerable to obstructions, particularly human blockage, posing significant challenges for reliable link prediction and network planning. Existing models often oversimplify human-induced attenuation, limiting their accuracy in real-world scenarios. This work addresses this gap by proposing a cylindrical diffraction model to quantify human blockage effects at 32.5 GHz—the first application of such a model at this frequency. Through controlled experiments, we measured signal degradation as a human subject progressively blocked a 2-meter mmWave link, revealing a sharp decline in received power from −41.2 dBm (no blockage) to −69.7 dBm (full blockage). The cylindrical model demonstrated strong alignment with empirical trends, accurately capturing the nonlinear increase in attenuation as the human approached the line-of sight path. Notably, the model matched baseline measurements within 1.4 dB and predicted full-blockage loss within 7 dB of observed values, despite inherent simplifications. This study underscores the efficacy of cylindrical modelling for mmWave blockage prediction while highlighting critical refinements needed for practical deployment, such as incorporating material properties and antenna radiation patterns. By bridging theoretical and empirical insights, our work provides a foundational framework for enhancing 5G/6G network resilience in human-dense environments, ensuring robust performance for high-data-rate applications. 

ZnO thin films were deposited on stainless steel substrates using the immersion method by immersing the

substrates in a sol-gel coating solution at temperatures of 70 °C and 80 °C for varying durations of (1, 2, 3, and 4minutes).

The results indicated that increasing the immersion time significantly influenced the film thickness. Optical measurements

showed that transmittance at a wavelength of 350nm increased with higher deposition temperatures. Additionally, the

Urbach tail energy increased with temperature, whereas the band gap (Eg) decreased markedly. Furthermore, the

electrical conductivity of the ZnO films improved with increased temperature and immersion time.

This study critically examines the short- and long-term linkages between foreign trade volume (TVR) and sustainable development (SD) in Libya’s unique post-conflict, resource-dependent economy over the period 1990–2022. Utilising autoregressive distributed lag (ARDL) modelling, it assesses TVR’s impact on Hickel’s Sustainable Development Index (SDI) a holistic metric that goes beyond GDP by integrating crucial environmental and human well-being indicators. The results reveal a positive long-term cointegration between TVR and the SDI, primarily driven by associated growth in GDP and GDP per capita. However, this relationship remains fragile, as persistent inflation and high unemployment significantly undermine sustainability gains. Libya’s structural overreliance on hydrocarbons and chronic macroeconomic instability are identified as the core impediments to balanced progress. The study recommends a strategic pivot towards diversifying exports, stabilising macroeconomic conditions, and implementing fair labour policies to better align trade growth with the Sustainable Development Goals (SDGs). Prioritising inflation control and fostering inclusive employment are paramount to enhancing Libya’s SDI resilience.

Asphalt roads are one of the most important elements of infrastructure in any country, as they play a vital role in achieving comprehensive development and economic growth. They provide safe and reliable means of transportation for citizens and companies, which develops trade, contributes to the development of industry, and expands the investment base. In addition, asphalt roads contribute to enhancing tourism and developing the infrastructure of cities and rural areas. Therefore, it is necessary to invest heavily in the construction and maintenance of asphalt roads to ensure economic growth and social stability. The Superpave system is an important development in the field of paving, as it contributes to improving the design of hot asphalt mixes and evaluating the performance of paving facilities. This system relies on precise standards to evaluate the quality of asphalt mixes, which leads to improving the durability of the pavement and its efficiency in withstanding different traffic loads. This system is also the result of field and laboratory research and studies included in the Strategic Highway Research Program in the United States of America. Due to the importance of this system, we present this study to examine previous studies on the classification of asphalt binders in the high-performance asphalt paving system (Superpave) and to identify the significance of classifying the binder in this system.

A recent years. They have evolved into analysis of tumor Abstract— Multiplexed platforms have become a standard feature of modern medicine in the field of histopathology in recent years. They have evolved into powerful technologies that enable image analysis of tumor tissues from formalin- fixed paraffin- embedded specimens, aiming for better assessment of morphology and distinctive alterations at the molecular level of the patient’s sample, which is critical for the pathologist’s diagnosis and classification, with significant implications for the following therapeutic options. And also, in order to gain a better understanding of the tumor microenvironment, which aids cancer prevention by simulating new therapy discoveries. And unlike traditional IHC, which can only identify one marker in a tissue sample, multiplex IHC may detect many markers in a single tissue sample while providing detailed information about the cell composition and spatial arrangement. Reviewing multiplexed technologies is to demonstrate their utility in the study of cancer tissue as well as their benefits for applications in cancer diagnosis, stratifying patients, and accuracy for treatment. Summary: Digital pathology plays a significant part in current clinical practice and becoming an increasingly critical technological necessity in the laboratory environment, Algorithms for image analysis and artificial intelligence have the potential to further increase the quality of diagnostics in pathology. Keywords— Digital pathology; Molecular diagnostics; IHC & MIHC Techniques; cancers.